10 citations · 12 across the 4 of their papers we have counts for
4 papers
HONEST-CAV: Hierarchical Optimization of Network Signals and Trajectories for Connected and Automated Vehicles with Multi-Agent Reinforcement Learning
Ziyan Zhang, Changxin Wan, Peng Hao +5
This study presents a hierarchical, network-level traffic flow control framework for mixed traffic consisting of Human-driven Vehicles (HVs), Connected and Automated Vehicles (CAVs…
MamBEV: Enabling State Space Models to Learn Birds-Eye-View Representations
Hongyu Ke, Jack Morris, Kentaro Oguchi +4
3D visual perception tasks, such as 3D detection from multi-camera images, are essential components of autonomous driving and assistance systems. However, designing computationally…
Cooperverse: A Mobile-Edge-Cloud Framework for Universal Cooperative Perception with Mixed Connectivity and Automation
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +3
Cooperative perception (CP) is attracting increasing attention and is regarded as the core foundation to support cooperative driving automation, a potential key solution to address…
Cyber Mobility Mirror for Enabling Cooperative Driving Automation in Mixed Traffic: A Co-Simulation Platform
Zhengwei Bai, Guoyuan Wu, Xuewei Qi +3
Endowed with automation and connectivity, Connected and Automated Vehicles are meant to be a revolutionary promoter for Cooperative Driving Automation. Nevertheless, CAVs need high…